Quality-Aware Network for Face Parsing

This is a very short technical report, which introduces the solution of the Team BUPT-CASIA for Short-video Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Challenge at CVPR 2021. Face parsing has recently attracted increasing interest due to its numerous application potentials. Generally speaking, it has a lot in common with human parsing, such as task setting, data characteristics, number of categories and so on. Therefore, this work applies state-of-the-art human parsing method to face parsing task to explore the similarities and differences between them. Our submission achieves 86.84% score and wins the 2nd place in the challenge.Comment: 2nd place in Short-video Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Challenge at CVPR 202

Production of Spin-Semiconducting Zigzag Graphene Nanoribbons by Constructing Asymmetric Notch on Graphene Edges

The electronic and magnetic properties of zigzag graphene nanoribbons with asymmetric notches along their edges are investigated by first principle density functional theory calculations. It is found that the electronic and magnetic properties of the asymmetrically-notched graphene nanoribbons are closely related with the depth of notches, but weekly dependent on the length of notches. As the relative depth of notch increases, the energy level of spin-up and spin-down becomes greatly shifted, associated with the gradual increase of magnetic momentum. The asymmetric band shift allows the asymmetrically notched graphene nanoribbons to be a spintronic semiconductor, through which an N- or P-type spin-semiconductor can be obtained by doping B or N atoms

Molecular identification and food source inference of constructive plants, native to the Ophiocordyceps sinensis habitat

Ophiocordyceps sinensis is a precious and effectual Traditional Chinese Medicine, native to Tibetan Plateau. Its development originated from parasitization of Hirsutella sinensis to Hepialus larvae, which was deemed to be of great importance including feeding food habit. Hereby in the present, study on food resource plants and their molecular identification technique were performed by some methods such as vegetation investigation, morphological taxonomy, sequence alignment, phylogenetic inference, primer design and correlation analysis and so on. In consequence, molecular identification system of constructive plants native to the O. sinensis habitat was established, and then feeding food habit of Hepialus pui larvae and its correlation with genesis mechanism of O. sinensis were preliminarily analyzed and discussed. It is very significant for phylogenetic systematicbotany research of plateau plants on a relative large scale, and it is the first time to study feeding food habit of Hepialus larvae and its related infected process on the molecular level.Keywords: Phylogenetic inference, molecular identification, constructive plant, Ophiocordyceps sinensis, Hepialus pu

Morphology-Enhanced CAM-Guided SAM for weakly supervised Breast Lesion Segmentation

Breast cancer diagnosis challenges both patients and clinicians, with early detection being crucial for effective treatment. Ultrasound imaging plays a key role in this, but its utility is hampered by the need for precise lesion segmentation-a task that is both time-consuming and labor-intensive. To address these challenges, we propose a new framework: a morphology-enhanced, Class Activation Map (CAM)-guided model, which is optimized using a computer vision foundation model known as SAM. This innovative framework is specifically designed for weakly supervised lesion segmentation in early-stage breast ultrasound images. Our approach uniquely leverages image-level annotations, which removes the requirement for detailed pixel-level annotation. Initially, we perform a preliminary segmentation using breast lesion morphology knowledge. Following this, we accurately localize lesions by extracting semantic information through a CAM-based heatmap. These two elements are then fused together, serving as a prompt to guide the SAM in performing refined segmentation. Subsequently, post-processing techniques are employed to rectify topological errors made by the SAM. Our method not only simplifies the segmentation process but also attains accuracy comparable to supervised learning methods that rely on pixel-level annotation. Our framework achieves a Dice score of 74.39% on the test set, demonstrating compareable performance with supervised learning methods. Additionally, it outperforms a supervised learning model, in terms of the Hausdorff distance, scoring 24.27 compared to Deeplabv3+'s 32.22. These experimental results showcase its feasibility and superior performance in integrating weakly supervised learning with SAM. The code is made available at: https://github.com/YueXin18/MorSeg-CAM-SAM

Prognostic Value of Vascular Endothelial Growth Factor Expression in Patients with Lung Cancer: A Systematic Review with Meta-Analysis

BackgroundVascular endothelial growth factor (VEGF) has been implicated in tumorigenesis and metastasis, and it presumably mediates the proliferation of endothelial cells and promotes vascular permeability. However, the prognostic value of VEGF overexpression in patients with lung cancer remains controversial.MethodsSurvival data from published studies were aggregated following a methodological assessment. A systematic review of eligible studies with meta-analysis was performed to quantitatively review the correlation of VEGF overexpression with survival in patients with lung cancer.ResultsWe conducted a final analysis of 5386 patients from 51 studies. The studies were categorized by histology, disease stage, patient race, VEGF isoform, and laboratory techniques used. Combined hazard ratios suggested that VEGF overexpression had an unfavorable impact on survival of patients with non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). However, VEGFC and vascular endothelial growth factor receptor 3 (VEGFR3)/flt-1 overexpression did not significantly correlate with survival in patients with NSCLC. In stage I–III NSCLC with VEGF, the hazard ratio (95% confidence interval) was 1.46 (1.38–1.54) overall, 1.35 (1.24–1.46) in Asian patients, 1.61 (1.49–1.73) in non-Asian patients, 1.41 (1.17–1.65) in SCLC, 1.27 (1.06–1.47) in adenocarcinoma, 1.57 (1.43–1.70) in stage I NSCLC, 1.46 (1.38–1.55) in NSCLC by immunohistochemistry, 1.52 (1.23–1.81) in NSCLC by reverse transcription-polymerase chain reaction, 1.22 (0.96–1.47) in NSCLC with VEGFC, and 1.58 (0.96–2.20) in NSCLC with VEGFR3/flt-1. The data collected were not sufficient to determine the prognostic value of VEGF in patients with squamous cell lung carcinomas.ConclusionVEGF overexpression indicates a poor prognosis for patients with NSCLC and SCLC; VEGFC and VEGFR3/flt-1 overexpression was not significantly correlated with survival for patients with NSCLC

Identification of miRNAs and their target genes in developing soybean seeds by deep sequencing

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) regulate gene expression by mediating gene silencing at transcriptional and post-transcriptional levels in higher plants. miRNAs and related target genes have been widely studied in model plants such as <it>Arabidopsis </it>and rice; however, the number of identified miRNAs in soybean (<it>Glycine max</it>) is limited, and global identification of the related miRNA targets has not been reported in previous research.</p> <p>Results</p> <p>In our study, a small RNA library and a degradome library were constructed from developing soybean seeds for deep sequencing. We identified 26 new miRNAs in soybean by bioinformatic analysis and further confirmed their expression by stem-loop RT-PCR. The miRNA star sequences of 38 known miRNAs and 8 new miRNAs were also discovered, providing additional evidence for the existence of miRNAs. Through degradome sequencing, 145 and 25 genes were identified as targets of annotated miRNAs and new miRNAs, respectively. GO analysis indicated that many of the identified miRNA targets may function in soybean seed development. Additionally, a soybean homolog of Arabidopsis SUPPRESSOR OF GENE SLIENCING 3 (<it>AtSGS3</it>) was detected as a target of the newly identified miRNA Soy_25, suggesting the presence of feedback control of miRNA biogenesis.</p> <p>Conclusions</p> <p>We have identified large numbers of miRNAs and their related target genes through deep sequencing of a small RNA library and a degradome library. Our study provides more information about the regulatory network of miRNAs in soybean and advances our understanding of miRNA functions during seed development.</p

Rosiglitazone Suppresses the Growth and Invasiveness of SGC-7901 Gastric Cancer Cells and Angiogenesis In Vitro via PPARγ Dependent and Independent Mechanisms

Although thiazolidinediones (TZDs) were found to be ligands for peroxisome proliferators-activated receptorγ (PPARγ), the mechanism by which TZDs exert their anticancer effect remains unclear. Furthermore, the effect of TZDs on metastatic and angiogenesis potential of cancer cells is unknown. Our results in this paper show that rosiglitazone inhibited SGC-7901 gastric cancer cells growth, caused G1 cell cycle arrest and induced apoptosis in a dose-dependent manner. The effects of rosiglitazone on SGC-7901 cancer cells were completely reversed by treatment with PPARγ antagonist GW9662. Rosiglitazone inhibited SGC-7901 cell migration, invasiveness, and the expression of MMP-2 in dose-dependent manner via PPARγ-independent manner. Rosiglitazone reduced the VEGF induced angiogenesis of HUVEC in dose-dependent manner through PPARγ-dependent pathway. Moreover, rosiglitazone did not affect the expression of VEGF by SGC-7901 cells. Our results demonstrated that by PPARγ ligand, rosiglitazone inhibited growth and invasiveness of SGC-7901 gastric cancer cells and angiogenesis in vitro via PPARγ-dependent or -independent pathway